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Stacked Denoising Autoencoders for Mortality Risk Prediction Using Imbalanced Clinical Data (2018)
Conference Proceeding
Alhassan, Z., McGough, A. S., Alshammari, R., Daghstani, T., Budgen, D., & Al Moubayed, N. (2018). Stacked Denoising Autoencoders for Mortality Risk Prediction Using Imbalanced Clinical Data. In 17th IEEE International Conference on Machine Learning and Applications (ICMLA) ; proceedings (541-546). https://doi.org/10.1109/icmla.2018.00087

Clinical data, such as evaluations, treatments, vital sign and lab test results, are usually observed and recorded in hospital systems. Making use of such data to help physicians to evaluate the mortality risk of in-hospital patients provides an inva... Read More about Stacked Denoising Autoencoders for Mortality Risk Prediction Using Imbalanced Clinical Data.

Enhanced detection of movement onset in EEG through deep oversampling (2017)
Conference Proceeding
Al Moubayed, N., Hasan, B. A. S., & McGough, A. S. (2017). Enhanced detection of movement onset in EEG through deep oversampling. In 2017 International Joint Conference on Neural Networks (IJCNN 2017) : Anchorage, Alaska, USA, 14-19 May 2017 (71-78). https://doi.org/10.1109/ijcnn.2017.7965838

A deep learning approach for oversampling of electroencephalography (EEG) recorded during self-paced hand movement is investigated for the purpose of improving EEG classification in general and the detection of movement onset during online Brain-Comp... Read More about Enhanced detection of movement onset in EEG through deep oversampling.

Identifying Changes in the Cybersecurity Threat Landscape using the LDA-Web Topic Modelling Data Search Engine (2017)
Book Chapter
Al Moubayed, N., Wall, D., & McGough, A. (2017). Identifying Changes in the Cybersecurity Threat Landscape using the LDA-Web Topic Modelling Data Search Engine. In T. Tryfonas (Ed.), Human aspects of information security, privacy and trust : 5th International Conference, HAS 2017, held as part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, proceedings (287-295). Springer Verlag. https://doi.org/10.1007/978-3-319-58460-7_19

Successful Cybersecurity depends on the processing of vast quantities of data from a diverse range of sources such as police reports, blogs, intelligence reports, security bulletins, and news sources. This results in large volumes of unstructured tex... Read More about Identifying Changes in the Cybersecurity Threat Landscape using the LDA-Web Topic Modelling Data Search Engine.

Using Machine Learning in Trace-driven Energy-Aware Simulations of High-Throughput Computing Systems (2017)
Conference Proceeding
McGough, A. S., Al Moubayed, N., & M, F. (2017). Using Machine Learning in Trace-driven Energy-Aware Simulations of High-Throughput Computing Systems. In Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion (ICPE '17 Companion), April 22 - 26, 2017, L’Aquila, Italy (55-60). https://doi.org/10.1145/3053600.3053612

When performing a trace-driven simulation of a High Throughput Computing system we are limited to the knowledge which should be available to the system at the current point within the simulation. However, the trace-log contains information we would n... Read More about Using Machine Learning in Trace-driven Energy-Aware Simulations of High-Throughput Computing Systems.

SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder (2016)
Conference Proceeding
Al Moubayed, N., Breckon, T., Matthews, P., & McGough, A. (2016). SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder. In A. E. P. Villa, P. Masulli, & A. J. Pons Rivero (Eds.), Artificial neural networks and machine learning – ICANN 2016 : 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016 ; proceedings. Part II (423-430). https://doi.org/10.1007/978-3-319-44781-0_50

In This paper we present a novel approach to spam filtering and demonstrate its applicability with respect to SMS messages. Our approach requires minimum features engineering and a small set of labelled data samples. Features are extracted using topi... Read More about SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder.

Multi-objective particle swarm optimisation: methods and applications (2014)
Thesis
Al Moubayed, N. (2014). Multi-objective particle swarm optimisation: methods and applications. (Thesis). Robert Gordon University. Retrieved from https://durham-repository.worktribe.com/output/1618029

Solving real life optimisation problems is a challenging engineering venture. Since the early days of research on optimisation it was realised that many problems do not simply have one optimisation objective. This led to the development of multi-obje... Read More about Multi-objective particle swarm optimisation: methods and applications.

Face-Based Automatic Personality Perception (2014)
Conference Proceeding
Al Moubayed, N., Vazquez-Alvarez, Y., McKay, A., & Vinciarelli, A. (2014). Face-Based Automatic Personality Perception. In Proceedings of the 22nd ACM international conference on Multimedia - MM '14, November 03–07, 2014, Orlando, FL, USA (1153-1156). https://doi.org/10.1145/2647868.2655014

Automatic Personality Perception is the task of automatically predicting the personality traits people attribute to others. This work presents experiments where such a task is performed by mapping facial appearance into the Big-Five personality trait... Read More about Face-Based Automatic Personality Perception.

D2MOPSO: MOPSO Based on Decomposition and Dominance with Archiving Using Crowding Distance in Objective and Solution Spaces (2014)
Journal Article
Al Moubayed, N., Petrovski, A., & McCall, J. (2014). D2MOPSO: MOPSO Based on Decomposition and Dominance with Archiving Using Crowding Distance in Objective and Solution Spaces. Evolutionary Computation, 22(1), 47-77. https://doi.org/10.1162/evco_a_00104

This paper improves a recently developed multi-objective particle swarm optimizer () that incorporates dominance with decomposition used in the context of multi-objective optimization. Decomposition simplifies a multi-objective problem (MOP) by trans... Read More about D2MOPSO: MOPSO Based on Decomposition and Dominance with Archiving Using Crowding Distance in Objective and Solution Spaces.

Continuous presentation for multi-objective channel selection in Brain-Computer Interfaces (2012)
Conference Proceeding
Al Moubayed, N., Awwad Shiekh Hasan, B., Gan, J., Petrovski, A., & McCall, J. (2012). Continuous presentation for multi-objective channel selection in Brain-Computer Interfaces. . https://doi.org/10.1109/cec.2012.6252991

A novel presentation for channel selection problem in Brain-Computer Interfaces (BCI) is introduced here. Continuous presentation in a projected two-dimensional space of the Electroencephalograph (EEG) cap is proposed. A multi-objective particle swar... Read More about Continuous presentation for multi-objective channel selection in Brain-Computer Interfaces.

Clustering based leaders' selection in multi-objective evolutionary algorithms (2011)
Conference Proceeding
Al Moubayed, N., Petrovski, A., & McCall, J. (2011). Clustering based leaders' selection in multi-objective evolutionary algorithms. In N. Krasnogor (Ed.), . https://doi.org/10.1145/2001858.2001913

Clustering-based Leaders Selection (CLS) is a novel leaders selection technique in multi-objective evolutionary algorithms. Clustering is applied on both the objective and solution spaces whereby each individual is assigned to two clusters; one in th... Read More about Clustering based leaders' selection in multi-objective evolutionary algorithms.

Multi-objective Optimisation of Cancer Chemotherapy using Smart PSO with Decomposition (2011)
Conference Proceeding
Al Moubayed, N., Petrovski, A., & McCall, J. (2011). Multi-objective Optimisation of Cancer Chemotherapy using Smart PSO with Decomposition. . https://doi.org/10.1109/smdcm.2011.5949264

The paper presents a novel approach to optimising cancer chemotherapy with respect to conflicting treatment objectives aimed at reducing the number of cancerous cells and at limiting the amounts of anti-cancer drugs used. The approach is based on the... Read More about Multi-objective Optimisation of Cancer Chemotherapy using Smart PSO with Decomposition.

Binary-SDMOPSO and its application in channel selection for Brain-Computer Interfaces (2010)
Conference Proceeding
Al Moubayed, N., Awwad Shiekh Hasan, B., Gan, J., Petrovski, A., & McCall, J. (2010). Binary-SDMOPSO and its application in channel selection for Brain-Computer Interfaces. . https://doi.org/10.1109/ukci.2010.5625570

In, we introduced Smart Multi-Objective Particle Swarm Optimisation using Decomposition (SDMOPSO). The method uses the decomposition approach proposed in Multi-Objective Evolutionary Algorithms based on Decomposition (MOEA/D), whereby a multi-objecti... Read More about Binary-SDMOPSO and its application in channel selection for Brain-Computer Interfaces.

Temporal White-Box Testing Using Evolutionary and Search-base Algorithms (2009)
Presentation / Conference
Al Moubayed, N., & Awwad Shiekh Hasan, B. (2009, December). Temporal White-Box Testing Using Evolutionary and Search-base Algorithms. Paper presented at 9th Annual Workshop on Computational Intelligence, Colchester, UK

Real-time embedded systems are constrained with real-time requirements. Assuring the quality of such systems is necessary especially in sensitive applications, i.e. where safety is an issue. This paper proposes novel methods for testing the temporal... Read More about Temporal White-Box Testing Using Evolutionary and Search-base Algorithms.

Temporal White-Box Testing Using Evolutionary Algorithms (2009)
Conference Proceeding
Al Moubayed, N., & Windisch, A. (2009). Temporal White-Box Testing Using Evolutionary Algorithms. . https://doi.org/10.1109/icstw.2009.17

Embedded computer systems should fulfill real-time requirements which need to be checked in order to assure system quality. This paper stands to propose some ideas for testing the temporal behavior of real-time systems. The goal is to achieve white-b... Read More about Temporal White-Box Testing Using Evolutionary Algorithms.

Signal Generation for Search-Based Testing of Continuous Systems (2009)
Conference Proceeding
Windisch, A., & Al Moubayed, N. (2009). Signal Generation for Search-Based Testing of Continuous Systems. . https://doi.org/10.1109/icstw.2009.16

Test case generation constitutes a critical activity in software testing that is cost-intensive, time-consuming and error-prone when done manually. Hence, an automation of this process is required. One automation approach is search-based testing for... Read More about Signal Generation for Search-Based Testing of Continuous Systems.